Ovarian cancer is the leading cause of death from gynecological malignancies mainly due to its late diagnosis, high mortality and low 5-year survival rates of only 30%. Reasons for this poor outcome include non specific presenting symptoms and identification in advanced stages of disease, mainly due to the absence of reliable screening methods for early detection. Ovarian cancer is the 6th most common cancer world-wide with 204,000 cases and 125,000 deaths worldwide. The exact cause of developing ovarian cancer is still unknown; however, women with certain risk factors may be more likely than others to develop ovarian cancer. The top ranking factors include age, parity (like for breast cancer), personal and drug history.
Besides the correct and timely diagnosis of ovarian cancer, its treatment poses major challenges. Advanced ovarian cancer patients frequently receive carboplatinum as standard chemotherapy. Most patients initially respond to this chemotherapy. However, up to 75% of initial platinum responders recur with chemoresistant tumor within the first 2 years and eventually succumb to metastatic disease. In addition, a small fraction of ovarian cancers are primarily refractory to platinum compounds.
Thus, information about how a cancer develops through molecular events could not only be very helpful for diagnostic purposes and allow to improve the clinical outcome in patients with cancer at its earliest stage, while it is still localized and readily treatable, but also allow a clinician to predict more accurately how such a cancer is likely to respond to specific therapeutic treatments. In this way, a regimen based on knowledge of the tumor's sensitivity can be rationally designed. Hence, characterization of a cancer patient in terms of predicting treatment outcome enables the physician to make an informed decision as to a therapeutic regimen with appropriate risk and benefit trade-offs to the patient.
US Patent application 20090011049 is related to the area of cancer prognosis and therapeutics and discloses aberrant methylation patterns of particular genes in cancers. Here, the silencing of nucleic acids encoding a DNA repair or DNA damage response enzyme was used prognostically and for selecting treatments that are tailored for an individual patient. Combinations of these markers were used to provide prognostic information.
Although several genes are reported to be differentially regulated in certain cancer types and cancer therapy resistance situations, it is difficult to integrate this information in order to predict a course of events for patients suffering from or being examined for cancer, in particular ovarian cancer, and to assess early therapeutic resistance, in particular a resistance to platinum based therapeutics.
There is thus a need for an improved method for providing cancer prognostic information, as well as assays and diagnostic methods based thereon.